{"id":18332132,"url":"https://github.com/oneoffcoder/lasso-bbn","last_synced_at":"2025-04-09T18:32:35.310Z","repository":{"id":106021399,"uuid":"396037262","full_name":"oneoffcoder/lasso-bbn","owner":"oneoffcoder","description":"Learning Bayesian Belief Networks with LASSO","archived":false,"fork":false,"pushed_at":"2022-04-26T17:31:14.000Z","size":15295,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-02-15T11:17:09.651Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/oneoffcoder.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-08-14T14:44:17.000Z","updated_at":"2022-01-26T05:39:41.000Z","dependencies_parsed_at":"2024-06-13T16:03:35.090Z","dependency_job_id":null,"html_url":"https://github.com/oneoffcoder/lasso-bbn","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oneoffcoder%2Flasso-bbn","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oneoffcoder%2Flasso-bbn/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oneoffcoder%2Flasso-bbn/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/oneoffcoder%2Flasso-bbn/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/oneoffcoder","download_url":"https://codeload.github.com/oneoffcoder/lasso-bbn/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248087650,"owners_count":21045558,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-05T19:37:33.382Z","updated_at":"2025-04-09T18:32:35.292Z","avatar_url":"https://github.com/oneoffcoder.png","language":"Jupyter Notebook","readme":"![pybbn logo](https://lasso-bbn.readthedocs.io/en/latest/_images/logo-250x250.png)\n\n# LASSO BBN\n\nLearning Bayesian Belief Networks (BBNs) with LASSO. Example code is as below. \n\n```python\nfrom lassobbn.learn import learn_parameters, learn_structure, to_bbn, to_join_tree, posteriors_to_df\n\n# Step 1. Learn the structure\ndf_path = './data/data-binary.csv'\nmeta_path = './data/data-binary-complete.json'\n\nparents = learn_structure(df_path, meta_path, n_way=2, ignore_neg_gt=-0.01, ignore_pos_lt=0.05)\n\n# Step 2. Learn the parameters\nd, g, p = learn_parameters(df_path, parents)\n\n# Step 3. Get the BBN\nbbn = to_bbn(d, g, p)\n\n# Step 4. Get the Join Tree\njt = to_join_tree(bbn)\n\n```\n\nYou can then use [Py-BBN](https://py-bbn.readthedocs.io/) to create a BBN and join tree (JT) instance and perform exact inference.\n\n# Installation\n\n```bash\npip install lassobbn\n```\n\n# Links\n\n- [Code](https://github.com/oneoffcoder/lasso-bbn)\n- [Documentation](https://lasso-bbn.readthedocs.io/en/latest/index.html)\n- [PyPi](https://pypi.org/project/lassobbn/)\n\n# Additional APIs\n\nturing_bbn                                                                            |  pyspark-bbn\n:------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------:\n![turing_bbn logo](https://turing-bbn.oneoffcoder.com/_images/turing-bbn-150x150.png) |![pyspark-bbn logo](https://pyspark-bbn.oneoffcoder.com/_images/pyspark-bbn-150x150.png)\n\n* [turing_bbn](https://turing-bbn.oneoffcoder.com/) is a C++17 implementation of py-bbn; take your causal and probabilistic inferences to the next computing level!\n* [pyspark-bbn](https://pyspark-bbn.oneoffcoder.com/) is a is a scalable, massively parallel processing MPP framework for learning structures and parameters of Bayesian Belief Networks BBNs using [Apache Spark](https://spark.apache.org/).\n\n# Citation\n\n```\n@misc{alemi_2021,\ntitle={lasso-bbn},\nurl={https://lasso-bbn.readthedocs.io/},\nauthor={F. Alemi, J. Vang},\nyear={2021},\nmonth={Aug}}\n```\n\n# Copyright Stuff\n\n## Software\n\n```\nCopyright 2021 Farrokh Alemi and Jee Vang\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n    http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n```\n\n## Art Copyright\n\nCopyright 2021 Daytchia Vang\n\n# Sponsor, Love\n\n- [Patreon](https://www.patreon.com/vangj)\n- [GitHub](https://github.com/sponsors/vangj)","funding_links":["https://www.patreon.com/vangj","https://github.com/sponsors/vangj"],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foneoffcoder%2Flasso-bbn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Foneoffcoder%2Flasso-bbn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Foneoffcoder%2Flasso-bbn/lists"}